Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{192121,
        author = {Mr. Aakash Anil Yadav and Miss. Priyanka Popat Jare and Mr. Tanmay Pradiprao Mahalle and Mr. Parag Nandkishor Bhoyar and Miss. Bhagyashri Namdeo Yadav and Miss. Suhani Gajanan Kamble and Prof. Sunil Panjabrao Chinte},
        title = {LawLens: AI-Based Legal Research and Case Summarization System for Indian Law},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {454-461},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192121},
        abstract = {The rapid growth of digitized legal documents in India, including court judgments, case records, and statutory texts, has introduced significant challenges in efficient legal research and comprehension. Legal documents are often lengthy, complex, and densely structured, requiring substantial time and expertise to analyze. While recent advancements in Natural Language Processing (NLP) and text summarization have shown promising results in generic domains, their application to the Indian legal system remains limited and largely jurisdiction-agnostic. Most existing legal summarization approaches are trained on foreign legal corpora and lack grounding in Indian constitutional provisions, leading to issues such as factual hallucinations, reduced legal relevance, and poor interpretability.
This paper presents LawLens, a concept-driven AI-based legal research and case summarization framework designed specifically for the Indian legal context. The proposed system emphasizes constitution-aware summarization by integrating retrieval mechanisms over the Indian Constitution and verified legal texts to support contextually grounded summaries. Rather than focusing on judgment prediction or legal decision-making, LawLens aims to function as an assistive tool for law students, junior advocates, and legal researchers by reducing document analysis time and improving comprehension. The paper systematically reviews existing legal document summarization techniques, identifies key research gaps, and proposes a structured system architecture and methodology to address these challenges. This study contributes a conceptual foundation for future development of legally grounded and explainable AI systems tailored to Indian law.},
        keywords = {Legal Document Summarization, Indian Law, Legal AI, Retrieval-Augmented Generation, Constitution-Aware NLP},
        month = {February},
        }